Structure-Based Design of Potent Aromatase Inhibitors by High-Throughput Docking

Pharmacophore-based virtual screening, molecular docking, and molecular dynamics investigation for the identification of novel, marine aromatase inhibitors

Breast cancer remains a leading cause of mortality among women worldwide. Our current research focuses on identifying effective therapeutic agents by targeting the human aromatase enzyme. Aromatase inhibitors (AIs) have been effective in treating postmenopausal breast cancer but face challenges such as drug resistance and long-term side effects like cognitive decline and osteoporosis. Natural products, especially from marine organisms, are emerging as potential sources for new drug candidates due to their structural diversity and pharmacological properties. This study aims to discover marine natural products capable of inhibiting human aromatase by combining ligand-based and structure-based pharmacophore models for virtual screening against the Comprehensive Marine Natural Products Database. From the initial virtual screening of more than 31,000 compounds, 1,385 marine natural products were identified as possible candidates. Following initial molecular docking analysis, only four compounds managed to pass the criteria this research has introduced to confirm strong binding affinity to aromatase. All four compounds yielded acceptable binding affinities, with CMPND 27987 having the highest -10.1 kcal/mol. All four hits were subjected to molecular dynamics, and CMPND 27987 was further confirmed to be the most stable at the protein's active site, with an MM-GBSA free binding energy of -27.75 kcal/mol. Our in silico studies indicate that CMPND 27987 interacts effectively within the binding site of the human aromatase, maintaining high affinity and stability. Based on these findings, we propose that CMPND 27987 could hold significant potential for further lead optimization and drug development.

The mode of toxic action of ionic liquids: Narrowing down possibilities using high-throughput, in vitro cell-based bioassays

Growing concerns about the environmental impact of ionic liquids (ILs) have spurred research into their (eco)toxic effects, but studies on their mode of toxic action (MOA) still remain limited. However, understanding the MOA and identifying structural features responsible for enhanced toxicity is crucial for characterising the hazard and designing safer alternatives. Therefore, 45 ILs, with systematically varied chemical structures, were tested for cytotoxicity and two specific endpoints in reporter gene assays targeting the Nrf2-ARE mediated oxidative stress response (AREc32) and aryl hydrocarbon receptor activation (AhR-CALUX). While none of the ILs activated the reporter genes, cytotoxicity was high and markedly different between cell lines. Seven and 25 ILs proved more cytotoxic than predicted by baseline toxicity model in the AREc32 and the AhR-CALUX assays, respectively. The length of the side chain and headgroup structures of ILs altered the MOA of ILs. Cellular metabolism of the ILs, investigated by LC-MS/MS, showed side-chain oxidation of the long-chain quaternary ammonium compounds in AhR-CALUX cells and, to a lower extent, in AREc32 cells, however, this transformation could not explain the high cytotoxicity. Effect data for 72 ILs for ten endpoints retrieved from the Tox21 database identified the inhibition of aromatase activity and of mitochondrial membrane potential as potential MOAs. However, in vitro fluorimetric assays for these endpoints demonstrated that effects were activated in a non-specific manner, probably through cytotoxicity. Although many of the ILs tested induced cytotoxicity at concentrations lower than baseline toxicity, the specific MOAs responsible could not be identified. Alternatively, we suggest that the descriptors currently used may fail to define the affinity of ILs for cells. Testing of the affinity of ILs for a diverse range of biomolecules is needed to accurately describe their interactions with cells.

Virtual screening, molecular docking, MD simulation studies, DFT calculations, ADMET, and drug likeness of Diaza-adamantane as potential MAPKERK inhibitors

Introduction: Multiple sclerosis (MS) is an autoimmune and inflammatory disease that destroys the protective coating of central nervous system (CNS) nerve fibers and affects over 2.8 million people worldwide. Despite several studies on new therapeutic targets and lead compounds, MS disease has limited treatment options. This condition may be caused by a complicated interaction of environmental and genetic variables. Studies showed that MS-associated microglial cells' increased MAPKERK activity may cause CNS inflammation and oligodendrocyte damage. Thus, screening for lead compounds that inhibit MAPKERK may protect brain cells and slow disease progression. Methods: The study aims to discover compounds that may inhibit MAPKERK as a novel approach for protecting the nervous system in managing MS. The study includes in silico methods, such as virtual screening, molecular docking, Density-functional theory (DFT) investigations (using the B3LYP/6-31++G(d,p) basis set in a gas phase environment), drug likeness scores, and molecular dynamic (MD) simulations. Results and Discussion:During the docking process with the MAPKERK protein, it was shown that the ligand L12 receptor had the best binding affinity, with a docking score of -6.18 kcal/mol. To investigate the stability of the binding, a 100 ns MD simulation was performed on the complex formed by the MAPKERK protein and L12. The receptor-ligand combination exhibited significant stability throughout the duration of the MD simulation. Additionally, the pharmacokinetic and drug-likeness properties of these ligands suggest that they have the potential to be considered viable candidates for future development in MS management.

New enantioenriched β-indolyl ketones as aromatase inhibitors: Unraveling heme-ligand interactions by MD simulation and MMPBSA analysis

A series of enantioenriched β-indolyl ketones as aromatase inhibitors (AI) is synthesized through the Michael-type Friedel-Crafts alkylation of indole. A highly efficient bifunctionalized amino catalyst is developed to access structurally diverse β-indolyl ketones in high yields (up to 91%) and excellent enantioselectivity (enantiomeric ratio up to 98:2). All the synthesized compounds demonstrated promising aromatase inhibitory potential, where ortho-substituted analogs (3c and 3e) were found most active with IC50 values of 0.68 and 0.90 µM, respectively. Both of these compounds exhibited significant cytotoxicity (IC50 = 0.34 and 0.37 µM) against the MCF-7 breast cancer cell line in the (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide) assay. Molecular docking studies of the synthesized compounds demonstrate favorable binding interactions with the estrogens controlling CYP19A1 (3EQM) and metabolizing CYP3A4 (5VCC) enzymes. Molecular dynamic (MD) simulation analysis revealed the essentiality of heme-ligand interactions to build a stable protein-ligand complex. An average root mean square deviation of 0.35 nm observed during a 100-ns MD simulation and binding free energy in the range of -190 to -227 kJ/mol calculated by g_mmpbsa analysis authenticated the stability of the 3c-3EQM complex. ADMET and drug-likeness parameters supported the suitability of these indole derivatives as the drug lead to develop potent inhibitors for estrogen-dependent breast cancer.

New 1,2,3-Triazole/1,2,4-triazole Hybrids as Aromatase Inhibitors: Design, Synthesis, and Apoptotic Antiproliferative Activity

A novel series of 1,2,3-triazole/1,2,4-triazole hybrids 5a, 5b, and 6a-i was designed and synthesized as antiproliferative agents targeting aromatase enzymes. The antiproliferative activity of the new hybrids against four cancer cells was studied using Erlotinib as a control. Compounds 6a and 6b demonstrated the highest antiproliferative activity among these hybrids, with GI50 values of 40 nM and 35 nM, respectively. Compound 6b was the most potent derivative, with a GI50 of 35 nM, comparable to Erlotinib's GI50 of 33 nM. Compound 6b inhibited all cancer cell lines with comparable efficacy to Erlotinib. Compounds 5a, 5b, and 6a-i were tested for inhibitory action against aromatase as a potential target for their antiproliferative activity. Results revealed that compounds 6a and 6b were the most potent aromatase inhibitors, with IC50 values of 0.12 ± 0.01 µM and 0.09 ± 0.01 µM, respectively, being more potent than the reference Ketoconazole (IC50 = 2.6 ± 0.20 µM) but less potent than Letrozole (IC50 = 0.002 ± 0.0002). These findings indicated that compounds 6a and 6b had significant aromatase inhibitory action and are potential antiproliferative candidates. The findings were further linked to molecular docking investigations, which gave models of strong interactions with the aromatase domain for inhibitors with high binding scores.

Synthesis, antiproliferative evaluation and in silico studies of a novel steroidal spiro morpholinone

Estrogens play a pivotal role in the development of estrogen-dependent breast cancer and other hormone-dependent disorders. A common strategy to overcome the pathological effects of estrogens is the use of aromatase inhibitors (AIs), which bind to the enzyme and prevent the union with the natural substrate, decreasing the amount of estrogens produced. Several AIs have been developed, including inhibitors with a steroidal backbone and a nitrogen heterocycle in their structure. Encouraged by the notable results presented by current and clinical steroidal drugs, herein we present the synthesis of a steroidal spiro morpholinone derivative as a plausible aromatase inhibitor. The morpholinone derivative was synthesized over a six-step methodology starting from estrone. The title compound and its hydroxychloroacetamide derivative precursor were evaluated for their antiproliferative profile against estrogen-dependent and independent solid tumor cell lines: A549, HBL-100, HeLa, SW1573, T-47D and WiDr. Both compounds exhibited a potent antiproliferative activity in the micromolar range against the six cancer cell lines, with the hydroxychloroacetamide derivative precursor being a more potent inhibitor (GI₅₀ = 0.25-2.4 µM) than the morpholinone derivative (GI₅₀ = 2.0-11 µM). Furthermore, both compounds showed, in almost all cases, better GI₅₀ values than the steroidal anticancer drugs abiraterone and galeterone. Docking simulations of the derivatives were performed in order to explain the experimental biological activity. The results showed interactions with the iron heme (derivative 3) and important residues of the steroidal binding-site (Met374) for the inhibition of human aromatase. A correlation was found between in vitro assays and the score obtained from the molecular docking study.

Synthesis of New Pyrimidine-Triazole Derivatives and Investigation of Their Anticancer Activities

Aromatase inhibitors are the most used anticancer drug group in breast cancer cases. The development of resistance in cancer patients over time and the side effects of existing drugs make the need for new and effective agents permanent. In this study, 10 novel pyrimidine-triazole derivatives were synthesized and their anticancer activities were investigated. Compounds  5c  and  5g  showed inhibitor activity against MCF-7 cell line with IC 50 =1.573±0.020; 3.698±0.056 µM value, respectively.  As a result of  in vitro  aromatase enzyme inhibition test, compounds  5c  and  5g  were exhibited significant activity with IC 50 =0.082±0.007 µM and IC50=0.198±0.015 µM, respectively. Estimated physicochemical parameters were calculated using the online SwissADME program for all compounds. Interaction modes of the compounds  5c  and  5g  were investigated against aromatase enzyme by means of docking studies. As a result of the studies, the importance of the triazole ring for aromatase inhibition has been understood.

Design, Semisynthesis, and Estrogenic Activity of Lignan Derivatives from Natural Dibenzylbutyrolactones

Based on molecular docking studies on the ERα, a series of lignan derivatives (3–16) were designed and semisynthesized from the natural dibenzylbutyrolactones bursehernin (1) and matairesinol dimethyl ether (2). To examine their estrogenic and antiestrogenic potencies, the effects of these compounds on estrogen receptor element (ERE)-driven reporter gene expression and viability in human ER+ breast cancer cells were evaluated. Lignan compounds induced ERE-driven reporter gene expression with very low potency as compared with the pure agonist E2. However, coincubation of 5 μM of lignan derivatives 1, 3, 4, 7, 8, 9, 11, 13, and 14 with increasing concentrations of E2 (from 0.01 pM to 1 nM) reduced both the potency and efficacy of pure agonists. The binding to the rhERα-LBD was validated by TR-FRET competitive binding assay and lignans bound to the rhERα with IC₅₀ values from 0.16 μM (compound 14) to 6 μM (compound 4). Induced fit docking (IFD) and molecular dynamics (MD) simulations for compound 14 were carried out to further investigate the binding mode interactions. Finally, the in silico ADME predictions indicated that the most potent lignan derivatives exhibited good drug-likeness.

Exploration of structural requirements for azole chemicals towards human aromatase CYP19A1 activity: Classification modeling, structure-activity relationships and read-across study

Human aromatase, also called CYP19A1, plays a major role in the conversion of androgens into estrogens. Inhibition of aromatase is an important target for estrogen receptor (ER)-responsive breast cancer therapy. Use of azole compounds as aromatase inhibitors is widespread despite their low selectivity. A toxicological evaluation of commonly used azole-based drugs and agrochemicals with respect to CYP19A1is currently requested by the European Union- Registration, Evaluation, Authorization and Restriction of Chemicals (EU-REACH) regulations due to their potential as endocrine disruptors. In this connection, identification of structural alerts (SAs) is an effective strategy for the toxicological assessment and safe drug design. The present study describes the identification of SAs of azole-based chemicals as guiding experts to predict the aromatase activity. Total 21 SAs associated with aromatase activity were extracted from dataset of 326 azole-based drugs/chemicals obtained from Tox21 library. A cross-validated classification model having high accuracy (error rate 5%) was proposed which can precisely classify azole chemicals into active/inactive toward aromatase. In addition, mechanistic details and toxicological properties (agonism/antagonism) of azoles with respect to aromatase were explored by comparing active and inactive chemicals using structure-activity relationships (SAR). Lastly, few structural alerts were applied to form chemical categories for read-across applications.

Pharmaceutical interest of in-silico approaches

The virtual environment within the computer using software performed on the computer is known as in-silico studies. These drugs designing software play a vital task in discovering new drugs in the field of pharmaceuticals. These designing programs and software are employed in gene sequencing, molecular modeling, and in assessing the three-dimensional structure of the molecule, which can further be used in drug designing and development. Drug development and discovery is not only a powerful, extensive, and an interdisciplinary system but also a very complex and time-consuming method. This book chapter mainly focused on different types of in-silico approaches along with their pharmaceutical applications in numerous diseases.

New azolyl-derivatives as multitargeting agents against breast cancer and fungal infections: synthesis, biological evaluation and docking study

Nonsteroidal aromatase inhibitors (NSAIs) are well-established drugs for the therapy of breast cancer. However, they display some serious side effects, and their efficacy can be compromised by the development of chemoresistance. Previously, we have reported different indazole-based carbamates and piperidine-sulphonamides as potent aromatase inhibitors. Starting from the most promising compounds, here we have synthesised new indazole and triazole derivatives and evaluated their biological activity as potential dual agents, targeting both the aromatase and the inducible nitric oxide synthase, being this last dysregulated in breast cancer. Furthermore, selected compounds were evaluated as antiproliferative and cytotoxic agents in the MCF-7 cell line. Moreover, considering the therapeutic diversity of azole-based compounds, all the synthesized compounds were also evaluated as antifungals on different Candida strains. A docking study, as well as molecular dynamics simulation, were carried out to shed light on the binding mode of the most interesting compound into the different target enzymes catalytic sites.

Synthesis, structure-activity relationships and molecular docking studies of phenyldiazenyl sulfonamides as aromatase inhibitors

The exploration of innovative aromatase inhibitors represents an important approach for the identification of new therapeutic treatments of breast cancer. In this respect, a series of phenyldiazenyl sulfonamides was designed, synthesized and tested. Compounds 3b, 3f and 5f showed an aromatase inhibition in the micromolar range and were evaluated in vitro on the human breast cancer cell line MCF7 by MTT assay, cytotoxicity assay (LDH release), cell cycle analysis and apoptosis, revealing a dose-dependent inhibition profile. In particular, 3f displayed the best reduction in terms of metabolic activity and an anti-proliferative effect on MCF7 cells, being blocked in the G1/S phase checkpoint. Moreover, computational studies were carried out to better understand at a molecular level of detail the rationale behind the effective binding to the active site of aromatase of the more active inhibitor 3f. The obtained results allow to consider this compound as an interesting lead for the development of a new class of non-steroidal aromatase inhibitors.

Targeting allosteric sites of human aromatase: a comprehensive in-silico and in-vitro workflow to find potential plant-based anti-breast cancer therapeutics

Recent findings suggested several allosteric pockets on human aromatase that could be utilised for the development of new modulators able to inhibit this enzyme in a new mechanism. Herein, we applied an integrated in-silico-based approach supported by in-vitro enzyme-based and cell-based validation assays to select the best leads able to target these allosteric binding sites from a small library of plant-derived natural products. Chrysin, apigenin, and resveratrol were found to be the best inhibitors targeting the enzyme’s substrate access channel and were able to produce a competitive inhibition with IC₅₀ values ranged from 1.7 to 15.8 µM. Moreover, they showed a more potent antiproliferative effect against ER+ (MCF-7) than ER- one (MDA-MB-231) cell lines. On the other hand, both pomiferin and berberine were the best hits for the enzyme’s haem-proximal cavity producing a non-competitive inhibition (IC₅₀ 15.1 and 21.4 µM, respectively) and showed selective antiproliferative activity towards MCF-7 cell lines.

Computing Metal-Binding Proteins for Therapeutic Benefit

Over one third of biomolecules rely on metal ions to exert their cellular functions. Metal ions can play a structural role by stabilizing the structure of biomolecules, a functional role by promoting a wide variety of biochemical reactions, and a regulatory role by acting as messengers upon binding to proteins regulating cellular metal-homeostasis. These diverse roles in biology ascribe critical implications to metal-binding proteins in the onset of many diseases. Hence, it is of utmost importance to exhaustively unlock the different mechanistic facets of metal-binding proteins and to harness this knowledge to rationally devise novel therapeutic strategies to prevent or cure pathological states associated with metal-dependent cellular dysfunctions. In this compendium, we illustrate how the use of a computational arsenal based on docking, classical, and quantum-classical molecular dynamics simulations can contribute to extricate the minutiae of the catalytic, transport, and inhibition mechanisms of metal-binding proteins at the atomic level. This knowledge represents a fertile ground and an essential prerequisite for selectively targeting metal-binding proteins with small-molecule inhibitors aiming to (i) abrogate deregulated metal-dependent (mis)functions or (ii) leverage metal-dyshomeostasis to selectively trigger harmful cells death.

Decision Making in Structure-Based Drug Discovery: Visual Inspection of Docking Results

Molecular docking is a computational method widely used in drug discovery. Due to the inherent inaccuracies of molecular docking, visual inspection of binding modes is a crucial routine in the decision making process of computational medicinal chemists. Despite its apparent importance for medicinal chemistry projects, guidelines for the visual docking pose assessment have been hardly discussed in the literature. Here, we review the medicinal chemistry literature with the aim of identifying consistent principles for visual inspection, highlighting cases of its successful application, and discussing its limitations. In this context, we conducted a survey reaching experts in both academia and the pharmaceutical industry, which also included a challenge to distinguish native from incorrect poses. We were able to collect 93 expert opinions that offer valuable insights into visually supported decision-making processes. This perspective shall motivate discussions among experienced computational medicinal chemists and guide young scientists new to the field to stratify their compounds.

Design, synthesis and biological evaluation of imidazole and triazole-based carbamates as novel aromatase inhibitors

In the search for novel aromatase inhibitors, a series of triazole and imidazole-based carbamate derivatives were designed and synthesized. Final compounds were thus evaluated against human aromatase by in vitro kinetic experiments in a fluorimetric assay in comparison with letrozole. The effect of most active derivatives 13a and 15c was then evaluated in vitro on the human breast cancer cell line MCF7 by MTT assay, cytotoxicity assay (LDH release) and cell cycle analysis, revealing a dose-dependent inhibition profile of cell viability and low micromolar IC₅₀ values. In addition, docking simulations were also carried out to elucidate at a molecular level of detail the binding modes adopted to target human aromatase.

Targeting Orthosteric and Allosteric Pockets of Aromatase via Dual-Mode Novel Azole Inhibitors

Breast cancer (BC) is the most diffused cancer type in women and the second leading cause of death among the female population. Effective strategies to fight estrogen responsive (ER+) BC, which represents 70% of all BC cases, rely on estrogen deprivation, via the inhibition of the aromatase enzyme, or the modulation of its cognate estrogen receptor. Current clinical therapies significantly increased patient survival time. Nevertheless, the onset of resistance in metastatic BC patients undergoing prolonged treatments is becoming a current clinical challenge, urgently demanding to devise innovative strategies. In this context, here we designed, synthesized, and performed in vitro inhibitory tests on the aromatase enzyme and distinct ER+/ER- BC cell line types of novel azole bridged xanthones. These compounds are active in the low μM range and behave as dual-mode inhibitors, targeting both the orthosteric and the allosteric sites of the enzyme placed along one access channel. Classical and quantum-classical molecular dynamics simulations of the new compounds, as compared with selected steroidal and nonsteroidal inhibitors, provide a rationale to the observed inhibitory potency and supply the guidelines to boost the activity of inhibitors able to exploit coordination to iron and occupation of the access channel to modulate estrogen production.

Adenosine Derivates as Antioxidant Agents: Synthesis, Characterization, in Vitro Activity, and Theoretical Insights

In this work, we present results about the synthesis and the antioxidant properties of seven adenosine derivatives. Four of these compounds were synthesized by substituting the N6-position of adenosine with aliphatic amines, and three were obtained by modification of the ribose ring. All compounds were obtained in pure form using column chromatography, and their structures were elucidated by infrared spectroscopy (IR) and Nuclear Magnetic Resonance (NMR). All adenosine derivatives were further evaluated in vitro as free radical scavengers. Our results show that compounds 1c, 3, and 5 display a potent antioxidant effect compared with the reference compound ascorbic acid. In addition, the absorption, distribution, metabolism and excretion (ADME) calculations show favorable pharmacokinetic parameters for the set of compounds analyzed, which guarantees their suitability as potential antioxidant drugs. Furthermore, theoretical analyses using Molecular Quantum Similarity and reactivity indices were performed in order to discriminate the different reactive sites involved in oxidative processes.

Discovery of Novel TASK-3 Channel Blockers Using a Pharmacophore-Based Virtual Screening

TASK-3 is a two-pore domain potassium (K_2P) channel highly expressed in the hippocampus, cerebellum, and cortex. TASK-3 has been identified as an oncogenic potassium channel and it is overexpressed in different cancer types. For this reason, the development of new TASK-3 blockers could influence the pharmacological treatment of cancer and several neurological conditions. In the present work, we searched for novel TASK-3 blockers by using a virtual screening protocol that includes pharmacophore modeling, molecular docking, and free energy calculations. With this protocol, 19 potential TASK-3 blockers were identified. These molecules were tested in TASK-3 using patch clamp, and one blocker (DR16) was identified with an IC₅₀ = 56.8 ± 3.9 μM. Using DR16 as a scaffold, we designed DR16.1, a novel TASK-3 inhibitor, with an IC₅₀ = 14.2 ± 3.4 μM. Our finding takes on greater relevance considering that not many inhibitory TASK-3 modulators have been reported in the scientific literature until today. These two novel TASK-3 channel inhibitors (DR16 and DR16.1) are the first compounds found using a pharmacophore-based virtual screening and rational drug design protocol.

Efficient synthesis and antioxidant activity of novel N-propargyl tetrahydroquinoline derivatives through the cationic Povarov reaction

New N-propargyl tetrahydroquinolines 6a-g have been synthesized efficiently through the cationic Povarov reaction (a domino Mannich/Friedel-Crafts reaction), catalyzed by Indium (III) chloride (InCl3), from the corresponding N-propargylanilines preformed, formaldehyde and N-vinylformamide, with good to moderate yields. All tetrahydroquinoline derivatives obtained were evaluated in vitro as free radical scavengers. Results showed that compound 6c presents a potent antioxidant effect compared with ascorbic acid, used as a reference compound. ADME predictions also revealed favorable pharmacokinetic parameters for the synthesized compounds, which warrant their suitability as potentials antioxidant. Additionally, a theoretical study using Molecular Quantum Similarity and reactivity indices were developed to discriminate different reactive sites in the new molecules in which the oxidative process occurs.

A network pharmacology study on the triterpene saponins from Medicago sativa L. for the treatment of Neurodegenerative diseases

Neurodegenerative diseases (NDDs) are characterized by progressive and irreversible, is a kind of complex illnesses, and the long-term therapy which is frequently associated with adverse side effects. Medicago sativa L., widely consumed as a vegetable, has the effects of improving memory and relieving central nervous system diseases. However, there are less studies on its specific mechanism for NDDs. In this investigation, we applied a method of network pharmacology, which combined molecular docking and network analysis to decipher the mechanisms of M. sativa in NDDs. The pharmacological system generated 55 triterpene saponins from M. sativa, and predicted 27 potential targets with 100 pathways in the treatment of NDDs. As a result, 13 compounds, 10 target proteins, and 6 signaling pathways were found to play important roles in the treatment of NDDs. In addition, in vitro experiments of isolates confirmed activities for NDDs, which were consistent with the results of network pharmacology prediction. PRACTICAL APPLICATIONS: Medicago sativa L. has been widely consumed as a vegetable, which possesses many nutritional components. As a functional food stuff, M. sativa can improve human health, such as memory improving activities, relieving central nervous system diseases, immunomodulatory, antioxidant, anticancer, and anti-inflammatory. In this article, the mechanism of triterpene saponins from M. sativa against NDDs was successfully predicted by network pharmacology method. The results will serve as a reference of M. sativa against NDDs.

Human cytochrome P450 enzymes 5-51 as targets of drugs and natural and environmental compounds: mechanisms, induction, and inhibition - toxic effects and benefits

Cytochrome P450 (P450, CYP) enzymes have long been of interest due to their roles in the metabolism of drugs, pesticides, pro-carcinogens, and other xenobiotic chemicals. They have also been of interest due to their very critical roles in the biosynthesis and metabolism of steroids, vitamins, and certain eicosanoids. This review covers the 22 (of the total of 57) human P450s in Families 5-51 and their substrate selectivity. Furthermore, included is information and references regarding inducibility, inhibition, and (in some cases) stimulation by chemicals. We update and discuss important aspects of each of these 22 P450s and questions that remain open.

Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery?

Metallo-enzymes are a large class of biomolecules promoting specialized chemical reactions. Quantum-classical quantum mechanics/molecular mechanics molecular dynamics, describing the metal site at quantum mechanics level, while accounting for the rest of system at molecular mechanics level, has an accessible time-scale limited by its computational cost. Hence, it must be integrated with classical molecular dynamics and enhanced sampling simulations to disentangle the functions of metallo-enzymes. In this review, we provide an overview of these computational methods and their capabilities. In particular, we will focus on some systems such as CYP19A1 a Fe-dependent enzyme involved in estrogen biosynthesis, and on Mg2+-dependent DNA/RNA processing enzymes/ribozymes and the spliceosome, a protein-directed ribozyme. This information may guide the discovery of drug-like molecules and genetic manipulation tools.

The Catalytic Mechanism of Steroidogenic Cytochromes P450 from All-Atom Simulations: Entwinement with Membrane Environment, Redox Partners, and Post-Transcriptional Regulation

Cytochromes P450 (CYP450s) promote the biosynthesis of steroid hormones with major impact on the onset of diseases such as breast and prostate cancers. By merging distinct functions into the same catalytic scaffold, steroidogenic CYP450s enhance complex chemical transformations with extreme efficiency and selectivity. Mammalian CYP450s and their redox partners are membrane-anchored proteins, dynamically associating to form functional machineries. Mounting evidence signifies that environmental factors are strictly intertwined with CYP450s catalysis. Atomic-level simulations have the potential to provide insights into the catalytic mechanism of steroidogenic CYP450s and on its regulation by environmental factors, furnishing information often inaccessible to experimental means. In this review, after an introduction of computational methods commonly employed to tackle these systems, we report the current knowledge on three steroidogenic CYP450s—CYP11A1, CYP17A1, and CYP19A1—endowed with multiple catalytic functions and critically involved in cancer onset. In particular, besides discussing their catalytic mechanisms, we highlight how the membrane environment contributes to (i) regulate ligand channeling through these enzymes, (ii) modulate their interactions with specific protein partners, (iii) mediate post-transcriptional regulation induced by phosphorylation. The results presented set the basis for developing novel therapeutic strategies aimed at fighting diseases originating from steroid metabolism dysfunction.

Novel Alkylimidazolium Ionic Liquids as an Antibacterial Alternative to Pathogens of the Skin and Soft Tissue Infections

Keeping in mind the concept of green chemistry, this research aims to synthesize and characterize new ionic liquids (ILs) derived from N-cinnamyl imidazole with different sizes of alkyl chains (1, 6, 8, and 10 carbon atoms), and evaluate their antibacterial activity against Skin and soft tissue infections (SSTIs) causative bacteria. The antibacterial screening was carried out by agar well diffusion and the Minimum Inhibitory Concentration (MIC) and Half Maximum Inhibitory Concentration (IC₅₀) of the different ILs were determined by microdilution in broth, also Molecular dynamics simulations were performed to study the interaction mechanism between ILs and membranes. The MIC value in Gram-positive bacteria showed that as the hydrocarbon chain increases, the MIC value decreases with a dose-dependent effect. Furthermore, Gram-negative bacteria showed high MIC values, which were also evidenced in the antibacterial screening. The molecular dynamics showed an incorporation of the ILs with the longer chain (10 C), corresponding to a passive diffusion towards the membrane surface, for its part, the ILs with the shorter chain due to its lack of hydrophobicity was not incorporated into the bilayer. Finally, the new ILs synthesized could be an alternative for the treatment of Gram-positive bacteria causative of SSTIs.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

Structure-activity relationships and docking studies of synthetic 2-arylindole derivatives determined with aromatase and quinone reductase 1

In our ongoing effort of discovering anticancer and chemopreventive agents, a series of 2-arylindole derivatives were synthesized and evaluated toward aromatase and quinone reductase 1 (QR1). Biological evaluation revealed that several compounds (e.g., 2d, IC50 = 1.61 μM; 21, IC50 = 3.05 μM; and 27, IC50 = 3.34 μM) showed aromatase inhibitory activity with half maximal inhibitory concentration (IC50) values in the low micromolar concentrations. With regard to the QR1 induction activity, 11 exhibited the highest QR1 induction ratio (IR) with a low concentration to double activity (CD) value (IR = 8.34, CD = 2.75 μM), while 7 showed the most potent CD value of 1.12 μM. A dual acting compound 24 showed aromatase inhibition (IC50 = 9.00 μM) as well as QR1 induction (CD = 5.76 μM) activities. Computational docking studies using CDOCKER (Discovery Studio 3.5) provided insight in regard to the potential binding modes of 2-arylindoles within the aromatase active site. Predominantly, the 2-arylindoles preferred binding with the 2-aryl group toward a small hydrophobic pocket within the active site. The C-5 electron withdrawing group on indole was predicted to have an important role and formed a hydrogen bond with Ser478 (OH). Alternatively, meta-pyridyl analogs may orient with the pyridyl 3'-nitrogen coordinating with the heme group.

In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods

Environmental chemicals may affect endocrine systems through multiple mechanisms, one of which is via effects on aromatase (also known as CYP19A1), an enzyme critical for maintaining the normal balance of estrogens and androgens in the body. Therefore, rapid and efficient identification of aromatase-related endocrine disrupting chemicals (EDCs) is important for toxicology and environment risk assessment. In this study, on the basis of the Tox21 10K compound library, in silico classification models for predicting aromatase binders/nonbinders were constructed by machine learning methods. To improve the prediction ability of the models, a combined classifier (CC) strategy that combines different independent machine learning methods was adopted. Performances of the models were measured by test and external validation sets containing 1336 and 216 chemicals, respectively. The best model was obtained with the MACCS (Molecular Access System) fingerprint and CC method, which exhibited an accuracy of 0.84 for the test set and 0.91 for the external validation set. Additionally, several representative substructures for characterizing aromatase binders, such as ketone, lactone, and nitrogen-containing derivatives, were identified using information gain and substructure frequency analysis. Our study provided a systematic assessment of chemicals binding to aromatase. The built models can be helpful to rapidly identify potential EDCs targeting aromatase.

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

Binding mode of triazole derivatives as aromatase inhibitors based on docking, protein ligand interaction fingerprinting, and molecular dynamics simulation studies

Aromatase inhibitors (AIs) as effective candidates have been used in the treatment of hormone-dependent breast cancer. In this study, we have proposed 300 structures as potential AIs and filtered them by Lipinski's rule of five using DrugLito software. Subsequently, they were subjected to docking simulation studies to select the top 20 compounds based on their Gibbs free energy changes and also to perform more studies on the protein-ligand interaction fingerprint by AuposSOM software. In this stage, anastrozole and letrozole were used as positive control to compare their interaction fingerprint patterns with our proposed structures. Finally, based on the binding energy values, one active structure (ligand 15) was selected for molecular dynamic simulation in order to get information for the binding mode of these ligands within the enzyme cavity. The triazole of ligand 15 pointed to HEM group in aromatase active site and coordinated to Fe of HEM through its N4 atom. In addition, two π-cation interactions was also observed, one interaction between triazole and porphyrin of HEM group, and the other was 4-chloro phenyl moiety of this ligand with Arg115 residue.

Unravelling exemestane: From biology to clinical prospects

Aromatase inhibitors (AIs) are anti-tumor agents used in clinic to treat hormone-dependent breast cancer. AIs block estrogens biosynthesis by inhibiting the enzyme aromatase, preventing tumor progression. Exemestane, a third-generation steroidal AI, belongs to this class of drugs and is currently used in clinic to treat postmenopausal women, due to its high efficacy and good tolerability. Here, its pharmacological and biological aspects as well as its clinical applications and comparison to other endocrine therapeutic agents, are reviewed. It is also focused the benefits and risks of exemestane, drawbacks to be overcome and aspects to be explored.

Flavonoids as CDK1 Inhibitors: Insights in Their Binding Orientations and Structure-Activity Relationship

In the last years, the interactions of flavonoids with protein kinases (PKs) have been described by using crystallographic experiments. Interestingly, different orientations have been found for one flavonoid inside different PKs and different chemical substitutions lead to different orientations of the flavonoid scaffold inside one PK. Accordingly, orientation predictions of novel analogues could help to the design of flavonoids with high PK inhibitory activities. With this in mind, we studied the binding modes of 37 flavonoids (flavones and chalcones) inside the cyclin-dependent PK CDK1 using docking experiments. We found that the compounds under study adopted two different orientations into the active site of CDK1 (orientations I and II in the manuscript). In addition, quantitative structure-activity relationship (QSAR) models using CoMFA and CoMSIA methodologies were constructed to explain the trend of the CDK1 inhibitory activities for the studied flavonoids. Template-based and docking-based alignments were used. Models developed starting from docking-based alignment were applied for describing the whole dataset and compounds with orientation I. Adequate R2 and Q2 values were obtained by each method; interestingly, only hydrophobic and hydrogen bond donor fields describe the differential potency of the flavonoids as CDK1 inhibitors for both defined alignments and subsets. Our current application of docking and QSAR together reveals important elements to be drawn for the design of novel flavonoids with increased PK inhibitory activities.

Promising Tools in Prostate Cancer Research: Selective Non-Steroidal Cytochrome P450 17A1 Inhibitors

Cytochrome P450 17A1 (CYP17A1) is an important target in the treatment of prostate cancer because it produces androgens required for tumour growth. The FDA has approved only one CYP17A1 inhibitor, abiraterone, which contains a steroidal scaffold similar to the endogenous CYP17A1 substrates. Abiraterone is structurally similar to the substrates of other cytochrome P450 enzymes involved in steroidogenesis, and interference can pose a liability in terms of side effects. Using non-steroidal scaffolds is expected to enable the design of compounds that interact more selectively with CYP17A1. Therefore, we combined a structure-based virtual screening approach with density functional theory (DFT) calculations to suggest non-steroidal compounds selective for CYP17A1. In vitro assays demonstrated that two such compounds selectively inhibited CYP17A1 17α-hydroxylase and 17,20-lyase activities with IC50 values in the nanomolar range, without affinity for the major drug-metabolizing CYP2D6 and CYP3A4 enzymes and CYP21A2, with the latter result confirmed in human H295R cells.